Everpure, formerly known as Pure Storage, is shifting from a storage-centric to a data-centric enterprise architecture, with new tools and updates to its Unified Data Plane.
Following its rebrand in February, Everpure is pivoting from its traditional storage focus to pursue a data management strategy. This week, the vendor unveiled what it calls a data primacy architecture, shipped a new product offering, Data Intelligence, based on its May 2026 acquisition of 1touch.io and a set of updates to its cloud platform to optimize data management for AI workloads. Everpure also unveiled another product, DataStream, a pipeline tool for converting unstructured enterprise data into an AI ready format.
Everpure's data primacy model aims to unify data from different application silos by embedding governance, context and semantics directly on the data layer. This gathers metadata and context into one location on the Everpure platform, as opposed to requiring organizations to copy or relocate data into each application that requires it for AI context.
"We see the world moving toward more of a data-centric view," said Prakash Darji, general manager of digital experience at Everpure. "Largely for the last 40 years, data and context have been encapsulated behind apps. In the world of agentic [AI], semantics are sprawled and encapsulated in apps that also fragment infrastructure. And as you fragment further, you end up with scale and manageability problems."
Prakash Darji
One analyst said it’s a good start for Evepure, but still questioned the company’s appeal to new customers.
"I think Everpure will have a really good shot within its storage portfolio to achieve primacy at the data layer," said Rob Strechay, an analyst at TheCube Research and Smuget Consulting. "Once you get outside of Everpure's gear, it becomes a bigger question mark."
Data intelligence and Everpure’s data management goals
Everpure Data Intelligence focuses on findin focuses on finding, cataloging and classifying enterprise data and applies governance and security controls,. Its three core capabilities are: universal discovery for visibility into structured and unstructured data; automated governance to scan systems to track compliance; and AI-ready context for mapping data and creating semantics knowledge graphs for agent querying.
"We've seen [instances] where extraneous data actually leads to poor outcomes versus focusing on data inputs," said Darji. "So largely for the last 40 years, data and context have been encapsulated behind apps."
Data Intelligence puts Everpure in competition with vendors such as Databricks, which have far more capabilities in areas such as automated governance. Databricks, for example, has a new offering called Genie Ontology for this purpose.
"Universal Discovery is very interesting," Strechay said. "Everpure will get a lot of people to use it, but when you start to look at other multi-cloud, multi-system, multi-vendor type hybrid tooling, that's very ambitious."
What is Everpure missing?
While Data Intelligence is a meaningful push toward data management for Everpure, the company still faces several gaps before it can compete with other data management organizations.
Largely for the last 40 years, data and context have been encapsulated behind apps.
Prakash Darjigeneral manager of digital experience at Everpure
One missing link is Everpure’s absence as an official member of the Open Semantic Interchange (OSI), an open source consortium that is building a shared standard for metadata and data catalog interoperability. It is backed by other data management companies such as Databricks, DBT and Snowflake.
"Everpure should be a part of that," Strechay said, noting that membership would put Everpure on equal footing with already established data management companies and give it easier access to the metadata context that it is pursuing.
"If they're really going down this path, they should be part of OSI with Snowflake and everybody else who's in there." Everpure also lacks its own database management system (DBMS) and the query and compute engine capabilities of s Apache Spark, Strechay noted.
Discovering data is only part of the challenge, Strechay said. Being able to catalog that data like competing data management companies is another;The context needs to live somewhere for agents to use it.
"This is a statement of the direction Everpure's going in," Strechay said. "But it's significantly behind others that are in that DBMS layer… Everpure has a lot of dots to connect between its heritage clients and 1touch.io," he said. "There's a gap."
An Everpure spokesperson said the company does not intend to add a DBMS. Instead, it plans to provide a semantic knowledge graph as agentic middleware that works with multiple sources of data, including databases, lakehouses and unstructured data repositories.
Unified Data Plane and Evergreen//One Overdrive
Everpure is making several other moves to help build out its new approach, includinga series of performance improvements and efficiency updates to its existing Unified Data Plane enterprise storage platform.
"Our unified data plane is focused on supporting all workloads continually with better and more performance as [AI agents] become more demanding," Darji said.
Another Unified Data Plane update adds support for the EverGreen//One Overdrive storage-as-a-service feature. This is an extension of its existing consumption model, enabling users to set storage reserves and pay for capacity on demand. EverGreen//One Overdrive can absorb traffic spikes up to 25% above a set baseline without requiring a permanent subscription upgrade.
The updates reflect a broader effort from Everpure to ensure its existing storage infrastructure can keep pace with the requirements of agentic AI workloads, as part of its overall data management shift, according to Strechay.
"What Everpure's trying to do there is reduce people feeling like they have to significantly over-provision systems… I think it's a smart thing for Everpure," Strechay said.
Alexander Gillis is a Technical Writer and Editor at Informa TechTarget, with more than 8 years of experience writing about technology.
Prakash Darji
